lc_get_ai_session_history

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must cover behavioral traits. It only says 'Fetch', implying a read operation, but does not disclose whether it is read-only, if authentication is needed, if it returns a large payload, or any side effects. This is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no unnecessary words. It conveys the core purpose efficiently, though it is quite short.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 parameters, no output schema, and no annotations. The description does not explain what 'bounded' means precisely, the format of session_id or oid, what the history contains, or what the return value looks like. This is inadequate for an AI agent to use the tool correctly without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, meaning the description must explain parameters. It only mentions 'bounded' vaguely, which could relate to the limit parameter, but does not explain oid or session_id at all. This adds negligible value over the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Fetch', the resource 'conversation history', and the scope 'for one org-scoped AI session'. It distinguishes itself from sibling tools like lc_get_ai_agent or lc_list_ai_sessions by specifying exactly what it retrieves.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives such as lc_get_ai_memory or lc_list_ai_sessions. The description does not state prerequisites, context, or situations where it should not be used.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.